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Seismic Vulneralbility Eatimation Analysis Of Reinforced Concrete Bridge

Posted on:2005-10-08Degree:MasterType:Thesis
Country:ChinaCandidate:P DuFull Text:PDF
GTID:2132360122991215Subject:Structural engineering
Abstract/Summary:PDF Full Text Request
The lifeline systems, such as highway transportation system,power supplysystem,water supply system,combustible gas system,medicine treatment systemand fire control system, etc. are very important to modern city. Subjected toearthquake, once the lifeline systems destroyed, the whole society will be greatlyhampered because of losing of municipal service function. So it is a very significanttask to predict disaster or vulnerability of the lifeline system. This dissertationmainly discussed the disaster prediction method of the bridge structures which aretaken from pratical urban disaster prevention. Vulnerability estimation analyses of bridges usually have to select someparameter or index to reflect their seismic resistance capacity, associate with actualearthquake,experiences and test results, and then to classify the damage stateaccording to different seismic parameters and hazard potentials. Vulnerabilityestimation analyses of bridges include estimation of economic loses besides damageprediction. This dissertation focuses on RC beam bridges and following results areattained: 1. Vulnerability estimation analyses for groups of highway bridges and railwaybridges are carried out in this dissertation. The seismic damage matrix is obtainedwhich gives the damage probability at the different levels of seismic intensityintuitively; 2. It is pointed that for important bridge, the damage prediction may beconducted following seismic design code to get damage assessment at differentlevels of earthquake input; 3. The finite element model is established to predict disaster of essential bridges,using the Push-over approach; 4. By using the conception of artificial neural network and correlated toolbox inMatlab, the disaster prediction for typical bridges as mentioned in first item of theresults is checked up. And the simulated results show the feasibility of this approach. In addition, the debris piling problem in earthquake forecast of thetransportation system is discussed. The new concepts of the effective width of roadand debris piling density are proposed which can be used to analyzed passage abilityof the hampered road. The method for estimating for traffic passage probability is IIABSTRACTimproved. The example analyses indicate that the improved formulation is moreproximately to the practical situation.
Keywords/Search Tags:bridge, disaster prediction, artificial neural network, debris piling
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